What transport modalities are supported for CT-e?

CT-e supports all modalities: road (rodoviário), air (aéreo), rail (ferroviário), waterway (aquaviário), pipeline (dutoviário) and multimodal.

When should I close an MDF-e?

You should close the MDF-e after the delivery is completed. Use the close_mdfe action to mark it as finished.

Can I cancel an authorized CT-e?

Yes, as long as it hasn't been used for transport yet. Use cancel_cte with a valid justification reason.

What documents are required to generate an MDF-e?

You need the related NFe (for own cargo) or CTe (for third-party cargo) references, as well as the vehicle's license plate and the driver's CPF.

Focus Logística MCP Server for Pydantic AI 7 tools — connect in under 2 minutes

Name: Focus Logística
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 7 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Focus Logística through the Vinkius and every tool is automatically validated against Pydantic schemas — catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Focus Logística "
            "(7 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Focus Logística?"
    )
    print(result.data)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Focus Logística MCP Server

Connect Focus Logística to any AI agent and manage your Brazilian cargo transport documentation — issue CT-e (Conhecimento de Transporte), MDF-e (Manifesto de Carga), close manifests, and download XMLs through natural conversation.

Pydantic AI validates every Focus Logística tool response against typed schemas, catching data inconsistencies at build time. Connect 7 tools through the Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code — full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Emit CT-e — Issue transport invoices for all modalities (road, air, rail, waterway)
Emit MDF-e — Create cargo manifests grouping multiple CT-e documents
Consult Status — Check authorization and current status of CT-e and MDF-e
Close Manifests — Mark MDF-e as finished/encerrado after delivery
Cancel Documents — Cancel CT-e with valid justification
Download XML — Retrieve XML for accounting and legal compliance

The Focus Logística MCP Server exposes 7 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Focus Logística to Pydantic AI via MCP

Follow these steps to integrate the Focus Logística MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 7 tools from Focus Logística with type-safe schemas

Why Use Pydantic AI with the Focus Logística MCP Server

Pydantic AI provides unique advantages when paired with Focus Logística through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture — switch between OpenAI, Anthropic, or Gemini without changing your Focus Logística integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Focus Logística connection logic from agent behavior for testable, maintainable code

Focus Logística + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Focus Logística MCP Server delivers measurable value.

Type-safe data pipelines: query Focus Logística with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Focus Logística tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Focus Logística and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Focus Logística responses and write comprehensive agent tests

Focus Logística MCP Tools for Pydantic AI (7)

These 7 tools become available when you connect Focus Logística to Pydantic AI via MCP:

cancel_cte

Cancel a CT-e

close_mdfe

Close/Finish a MDF-e

consult_cte

Consult CT-e status

consult_mdfe

Consult MDF-e status

download_xml

Download XML for CT-e or MDF-e

emit_cte

Emit a Conhecimento de Transporte (CT-e)

emit_mdfe

Emit Manifesto de Carga (MDF-e)

Example Prompts for Focus Logística in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Focus Logística immediately.

"Emit a CT-e for a freight of R$1,200.00 from SP to RJ."

"Close the MDF-e reference MDF-001."

"Download the XML for CT-e reference CTE-001."

Troubleshooting Focus Logística MCP Server with Pydantic AI

Common issues when connecting Focus Logística to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Focus Logística + Pydantic AI FAQ

Common questions about integrating Focus Logística MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer — your Focus Logística MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.